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Simulation study on dynamics transition in neuronal activity during sleep cycle by using asynchronous and symmetry
M Nakao1, T Takahashi, Y Mizutani
1Department of Information Engineering, Faculty of Engineering, Tohoku University, Sendai, Japan.
Biological Cybernetics
|January 1, 1990
Summary
Brain activity dynamics shift between sleep stages. Serotonergic system input influences neuronal power spectral densities, transitioning from white noise in slow wave sleep (SWS) to 1/f profiles in paradoxical sleep (PS).
Area of Science:
- Neuroscience
- Computational Neuroscience
- Sleep Science
Background:
- Single neuronal activity exhibits distinct dynamic transitions during the sleep-wake cycle in cats.
- Power spectral densities of neuronal activity shift from white noise profiles during slow wave sleep (SWS) to 1/f profiles during paradoxical sleep (PS).
- These global dynamics suggest an underlying common mechanism, potentially modulated by widespread inputs like the serotonergic system.
Purpose of the Study:
- To investigate the role of inhibitory input, representing the serotonergic system, in inducing neuronal dynamics transitions during the sleep cycle.
- To examine if varying inhibitory input levels can control the dynamics of single neuronal state evolution in a neural network model.
- To explore the relationship between network energy function geometry and inhibitory levels in driving these transitions.
Main Methods:
- Utilized an asynchronous and symmetric neural network model incorporating inhibitory input.
- Simulated the effects of varying global inhibitory input levels on neuronal dynamics.
- Analyzed power spectral density profiles and state evolution within the artificial neural network.
Main Results:
- Weak global inhibition resulted in 1/f-like power spectral density profiles, potentially corresponding to paradoxical sleep (PS).
- Strong global inhibition produced white noise profiles, potentially corresponding to slow wave sleep (SWS).
- The level of inhibition influenced the geometrical structure of the network's energy function, correlating with observed dynamics transitions.
Conclusions:
- The findings support the hypothesis that a globally applied inhibitory input, mimicking the serotonergic system, can drive the observed dynamics transitions in neuronal activity during the sleep cycle.
- The serotonergic system is suggested to be essential for modulating neuronal dynamics between different sleep stages.
- The study highlights the importance of network-level inhibitory mechanisms in regulating brain state transitions.